arXiv subjects

Sagnik Dutta

Publications and source records attributed to Sagnik Dutta.

6 recordsLinked to original sources

arXiv2026

The Complexity of Bisimilarity and Model Checking in Finitary Diagrams

Inspired by the work of Dubut, Goubault, and Goubault-Larrecq (ICALP 2015) on natural homology, Dubut (RAMiCS 2020) introduces finitary diagrams and studies bisimilarity and diagrammatic path logics for them. To this aim, he defines a fragment of the existential theory of the reals, called the existential theory of invertible matrices (ETIM). Using a PSPACE upper bound for this fragment, he proves that for finitary diagrams, bisimilarity can be decided in EXPSPACE and model checking for diagrammatic path logic in PSPACE. We significantly improve both these bounds and settle the complexity of model checking for finitary diagrams. As our first main result, we show that there is an efficient randomized algorithm for ETIM. Combining this with the previous work by Dubut, we obtain an NEXP upper bound for bisimilarity of finitary diagrams and an NP upper bound for diagrammatic path logic. We also provide a matching NP-hardness proof for the latter. The hardness proof introduces constrained layered poset problems, which may be of independent interest, and connects them to finitary diagrams using Gabriel's theorem for representations of path quivers. For bisimilarity over finite fields, we further improve the upper bound to PSPACE. In ETIM, we quantify over invertible matrices. We finally ask what happens if we instead quantify over matrices from the special linear group, that is, of determinant one. We show that in this case, the resulting fragment is equivalent to the existential theory of the reals, under a mild generalization of the allowed linear constraints.

cs.LO↗

arXiv2025

Problems from Optimization and Computational Algebra Equivalent to Hilbert's Nullstellensatz

Efficient algorithms for many problems in optimization and computational algebra often arise from casting them as systems of polynomial equations. Blum, Shub, and Smale formalized this as Hilbert's Nullstellensatz Problem $HN_R$: given multivariate polynomials over a ring $R$, decide whether they have a common solution in $R$. We can also view $HN_R$ as a complexity class by taking the downward closure of the problem $HN_R$ under polynomial-time many-one reductions. In this work, we show that many important problems from optimization and algebra are complete or hard for this class. We first consider the Affine Polynomial Projection Problem: given polynomials $f,g$, does an affine projection of the variables transform $f$ into $g$? We show that this problem is at least as hard as $HN_F$ for any field $F$. Then we consider the Sparse Shift Problem: given a polynomial, can its number of monomials be reduced by an affine shift of the variables? Prior $HN_R$-hardness for this problem was known for non-field integral domains $R$, which we extend to fields. For the special case of the real field, HN captures the existential theory of the reals and its complement captures the universal theory of the reals. We prove that the problems of deciding real stability, convexity, and hyperbolicity of a given polynomial are all complete for the universal theory of the reals, thereby pinning down their exact complexity.

cs.CC↗

arXiv2022

Classification and Quantification of Entanglement Through Wedge Product and Geometry

Wedge product of post-measurement vectors leading to an `area' measure of the parallelogram has been shown to give the generalized I-concurrence measure of entanglement. Extending the wedge product formalism to multi qudit systems, we have presented a modified faithful entanglement measure, incorporating the higher dimensional volume and the area elements of the parallelepiped formed by the post-measurement vectors. The measure fine grains the entanglement monotone, wherein different entangled classes manifest with different geometries. We have presented a complete analysis for the bipartite qutrit case considering all possible geometric structures. Three entanglement classes can be identified with different geometries of post-measurement vectors, namely three planar vectors, three mutually orthogonal vectors, and three vectors that are neither planar and not all of them are mutually orthogonal. It is further demonstrated that the geometric condition of area and volume maximization naturally leads to the maximization of entanglement. The wedge product approach uncovers an inherent geometry of entanglement and is found to be very useful for characterization and quantification of entanglement in higher dimensional systems.

quant-ph↗

arXiv2021

Absolutely Secure Distributed Superdense Coding: Entanglement Requirement for Optimality

Superdense coding uses entanglement as a resource to communicate classical information securely through quantum channels. A superdense coding method is optimal when its capacity reaches Holevo bound. We show that for optimality, maximal entanglement is a necessity across the bipartition of Alice and Bob, but neither absolute nor genuine multipartite entanglement is required. Unlike the previous schemes, which can transmit either even or odd bits of information, we have demonstrated a generalized dense coding protocol using the genuine multipartite entangled GHZ state to send arbitrary information bits. Expressed in the eigenbasis of different Pauli operators, GHZ state is characterized by a unique parity pattern which enables us to formulate a security checking technique to ensure absolute security of the protocol. We show this method to be equally applicable in a scenario, where the resource information is distributed among spatially separated parties. Finally, optimizing the number of qubit(s) sent to Bob, we construct a distributed dense coding method, which completely depicts absolutely secure one way quantum communication between many to one party.

quant-ph↗

arXiv2020

Operational Characterization of Multipartite Nonlocal Correlations

Nonlocality, one of the most puzzling features of multipartite quantum correlation, has been identified as a useful resource for device-independent quantum information processing. Motivated by the resource theory of quantum entanglement recently an operational framework have been proposed by Gallego et al. [\href{https://doi.org/10.1103/PhysRevLett.109.070401}{Phys. Rev. Lett. 109, 070401 (2012)}] and Bancal et al. [\href{https://doi.org/10.1103/PhysRevA.88.014102}{Phys. Rev. A 88, 014102 (2013)}] that characterizes the nonlocal resource present in multipartite quantum correlations. While the bipartite no-signaling correlations allows a dichotomous classification -- local vs. nonlocal, in multipartite scenario the authors have shown existence of several types of nonlocality that are inequivalent under the proposed operational framework. In this work we present a finer characterization of multipartite no-signaling correlations based on the same operational framework. We also clarify a statement in Gallego et al.'s work that could be misinterpreted and make the conclusions of that work more precise here.

quant-ph↗

arXiv2020

Quantum Circuit Design Methodology for Multiple Linear Regression

Multiple linear regression assumes an imperative role in supervised machine learning. In 2009, Harrow et al. [Phys. Rev. Lett. 103, 150502 (2009)] showed that their HHL algorithm can be used to sample the solution of a linear system $\mathbf{Ax=b}$ exponentially faster than any existing classical algorithm, with some manageable caveats. The entire field of quantum machine learning gained considerable traction after the discovery of this celebrated algorithm. However, effective practical applications and experimental implementations of HHL are still sparse in the literature. Here, we demonstrate a potential practical utility of HHL, in the context of regression analysis, using the remarkable fact that there exists a natural reduction of any multiple linear regression problem to an equivalent linear systems problem. We put forward a $7$-qubit quantum circuit design, motivated from an earlier work by Cao et al. [Mol. Phys. 110, 1675 (2012)], to solve a $3$-variable regression problem, using only elementary quantum gates. We also implement the Group Leaders Optimization Algorithm (GLOA) [Mol. Phys. 109 (5), 761 (2011)] and elaborate on the advantages of using such stochastic algorithms in creating low-cost circuit approximations for the Hamiltonian simulation. We believe that this application of GLOA and similar stochastic algorithms in circuit approximation will boost time- and cost-efficient circuit designing for various quantum machine learning protocols. Further, we discuss our Qiskit simulation and explore certain generalizations to the circuit design.

quant-ph↗